AI memory built for years of data.

Fortiana brings together conversations, files, activity, and data scattered across tools and systems into memory that any AI model can draw on when needed.

What could block Wednesday’s mobile app launch?

I’ll check the latest approval status and test results.

Compiled4.8s11 sourcesJira+10

Two things. Apple still hasn’t approved the iOS version, and the final checkout test is still failing. Everything else passed this morning, the Android version is ready, and no other launch blockers remain.

AI memory has serious problems. Existing solutions don’t solve them. We started from scratch and changed how memory is built.

Remember everything from the start

Most AI memory lets a model choose what to store.

Benchmarks show popular AI memory products can miss more than 40% of what they are supposed to remember. Fortiana keeps all source data and processes it without using AI models.

Memory that stays up to date

Memory can keep both old and new information.

As history grows, accuracy can fall from 68% to 28%. Fortiana updates memory as decisions, approvals, and plans change, while preserving earlier history and sources.

Built for years of data from thousands of people

AI memory vendors promise enterprise-scale memory on their websites. They don’t show what it costs to build.

Based on official AI memory pricing, processing months of organizational data can cost hundreds of thousands of dollars and take days to weeks. Fortiana slashes both.

AI memory shouldn't cost six figuresor take days to build.

We compared Fortiana with leading AI memory systems on the same real company data: roughly six months of work at a 25-person company. Same task, same data. The gap was not close.

50 GB of company data

  • Jira
  • Confluence
  • Slack
  • Gmail
  • Google Drive
  • GitHub
99.98%

lower cost to build memory

than the lowest-cost system in our comparison

48×

faster to build usable memory

than the fastest system we compared

A different kind of scalable AI memory, built on deterministic language compilation instead of per-record LLM extraction.

The technology is shared. The jobs are not. Fortiana powers purpose-built products for everyday work, cybersecurity operations, and coding agents.

Fortiana Hartlib

01 / 02

Ask anything about your work.

It connects history across your tools, so you get answers no single source could provide.

What happened the last time we raised prices?
Compiled in2s7 sourcesStripe, Salesforce, Gmail, Zendesk, Slack, Google Drive, Notion

The price increase generated €84,000 in additional revenue in the first three months. It also led to 47 cancellations, 32 of them from customers who received less than 30 days’ notice.

Most customers whose price changed at renewal did not cancel. The review recommended giving existing customers 45 days’ notice and applying the new price at renewal. Neither recommendation is included in the current plan.

What should we carry forward this time?

Apply the new price immediately to new customers only. Give existing customers 45 days’ notice and apply the new price at renewal.

Last time, support volume started to spike two days after the announcement, so schedule extra support staff for the first week.

Fortiana Diple

02 / 02

Stop paying agents to rediscover your project.

Before work begins, the agent receives project context, including decisions the team has already made.

Codex~/dev/dashboardgpt-5.6-sol · high
Build the workspace usage dashboard with date filters, KPI cards, a weekly usage chart, and a recent activity table. Reuse the existing design system and verify mobile and desktop.
I’ll stage the project context, then inspect the mapped files before editing.
Called fortiana.stage_context({"task":"workspace usage dashboard","scope":"apps/web"})
16 linked sources · 8 relevant files [map] dashboard-shell.tsx — layout and state boundaries [map] usage-query.ts — date range and aggregation contract [map] metric-card.tsx — existing KPI composition [map] chart.tsx — owned chart contract … +4 related files [reuse] Card · Tabs · Select · ChartContainer · Table · Badge · +2 components [decision] UsageQuery owns date-range normalization. [history] Previous chart used raw colors and omitted the empty state. [verify] 390 / 768 / 1440 · loading / empty / populated · +4 checks
Explored
Read apps/web/src/features/usage/dashboard-shell.tsx
Read apps/web/src/features/usage/usage-query.ts
Read packages/ui/src/metric-card.tsx
Read packages/ui/src/chart.tsx
I’ll implement against the existing query and component contracts, then add focused state coverage.
Edited apps/web/src/features/usage/dashboard-shell.tsx(+2 -1)
12import { WorkspaceUsageDashboard } from "./workspace-usage-dashboard";
42 <UsageDashboardPlaceholder />
42 <WorkspaceUsageDashboard />
Edited apps/web/src/features/usage/workspace-usage-dashboard.tsx(+118 -0)
Edited apps/web/src/features/usage/usage-metrics.tsx(+62 -0)
Edited apps/web/src/features/usage/usage-chart.tsx(+87 -0)
Edited apps/web/src/features/usage/recent-activity-table.tsx(+53 -0)
Edited apps/web/src/features/usage/usage-dashboard.test.tsx(+48 -0)
Ran pnpm exec vitest run apps/web/src/features/usage/usage-dashboard.test.tsx && pnpm typecheck
✓ apps/web/src/features/usage/usage-dashboard.test.tsx (18 tests) … +4 lines (ctrl + t to view transcript)

Built the workspace usage dashboard across six files, reusing the existing query and UI contracts.

Focused tests and pnpm typecheck pass.

─ Worked for 4m 12s

Connect the sources you already use.

Fortiana builds memory from their history and keeps it up to date.

Memory everywhere it’s needed. Data only where you allow it.

SaaS

Start in minutes.

Sign up, connect your tools, and invite your team. We manage the infrastructure, models, scaling, and updates for you.

Self-hosted

Inside your environment.

Run Fortiana in your private cloud, VPC, or data center. Your data and models stay inside your infrastructure, fully under your control.

Air-gapped

Built for full isolation.

Fortiana runs fully offline, with no internet connection. Local models and dedicated hardware let it run in a fully disconnected environment.

Use Fortiana in the cloud or run it on your own infrastructure. No matter where it runs, memory stays under your control.

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